Transcription of Chapter 1: The Ladder of Causation
1 The Book of Why: The New Science of Cause and Effect Pearl and Mackenzie 1 Chapter 1: The Ladder of Causation In the I was probably six or seven years old when I first read the story of Adam and Eve in the Garden of Eden. My classmates and I were not at all surprised by God s capricious demands, forbidding Adam from eating from the Tree of Knowledge. Deities have their reasons, we thought. What we were more intrigued by was the idea that as soon as they ate from the Tree of Knowledge, Adam and Eve became conscious, like us, of their nakedness. As teenagers, our interest shifted slowly to the more philosophical sides of the story. (In Israeli schools, Genesis is read several times a year.) Of primary concern to us was the notion that the emergence of human knowledge was not a joyful process but a painful one, accompanied by disobedience, guilt, and punishment.
2 Was it worth giving up the carefree life of Eden? Some asked. Were the agricultural and scientific revolutions that followed worth the economic hardships, military conquests, and social injustices that modern life entails? Don t get me wrong: we were no creationists; even our teachers were Darwinists at heart. We knew, however, that the author who choreographed the story of Genesis struggled to answer the most pressing philosophical questions of his time. We likewise suspected that this story bore the cultural footprints of the actual process by which Homo sapiens gained dominion over our planet. What, then, was the sequence of steps in this speedy, super-evolutionary process? My interest in these questions waned in my early career as a professor of engineering, but it was reignited suddenly in the 1990s, when I was writing my book Causality, and came to confront the Ladder of Causation .
3 As I re-read Genesis for the hundredth time, I noticed a nuance that had somehow eluded my attention for all those years. When God finds Adam hiding in the garden, he asks: Have you Unedited working copy, do not quoteThe Book of Why: The New Science of Cause and Effect Pearl and Mackenzie 2 eaten from the tree which I forbade you? And Adam answers: The woman you gave me for a companion, she gave me fruit from the tree and I ate. What is this you have done? God asks Eve. She replies: The serpent deceived me, and I ate. As we know, this blame game did not work very well on the Almighty, who banished both of them from the garden. The interesting thing, though, is that God asked what and they answered why. God asked for the facts, and they replied with explanations.
4 Moreover, both were thoroughly convinced that naming causes would somehow paint their actions in a different color. Where did they get this idea? For me, these nuances carried three profound messages. First, that very early in our evolution, humans came to realize that the world is not made up only of dry facts (what we might call data today), but that these facts are glued together by an intricate web of cause-effect relationships. Second, that causal explanations, not dry facts, make up the bulk of our knowledge, and that satisfying our craving for explanation should be the cornerstone of machine intelligence. Finally, that our transition from processors of data to makers of explanations was not gradual it required an external push from an uncommon fruit.
5 This matched perfectly what I observed theoretically in the Ladder of Causation : no machine can derive explanations from raw data. It needs a push. If we seek confirmation of these messages from evolutionary science, we of course won t find the Tree of Knowledge, but we still see a major unexplained transition. We understand now that humans evolved from ape-like ancestors over a period of 5-6 million years, and that such gradual evolutionary processes are not uncommon to life on Earth. But in roughly the last 50,000 years, something unique happened, which some call the Cognitive Revolution and others (with a touch of irony) call the Great Leap Forward. Humans acquired the ability to modify their environment and their own abilities at a dramatically faster rate.
6 The Book of Why: The New Science of Cause and Effect Pearl and Mackenzie 3 For example, over millions of years, eagles and owls have evolved truly amazing eyesight yet they never evolved eyeglasses, microscopes, telescopes, or night-vision goggles. Humans have produced these miracles in a matter of centuries. I call this phenomenon the super-evolutionary speedup. Some readers might object to my comparing apples and oranges, evolution to engineering, but that is exactly my point. Evolution has endowed us with the ability to engineer our lives, a gift she has not bestowed upon eagles and owls, and the question is again, Why? What computational facility did humans suddenly acquire that eagles lacked? Many theories have been proposed, but there is one I like because it is especially pertinent to the idea of Causation .
7 In his book Sapiens, historian Yuval Harari posits that our ancestors capacity to imagine non-existent things was the key to everything, for it allowed them to communicate better. Before this change, they could only trust people from their immediate family or tribe. Afterward their trust extended to larger communities, bound by common beliefs and common expectations (for example, beliefs in invisible yet imaginable deities, in the afterlife, and in the divinity of the leader). Whether you agree with Harari s theory or not, the connection between imagining and causal relations is almost self-evident. It is useless to know the causes of things unless you can imagine their consequences. Conversely, you cannot claim that Eve caused you to eat from the tree unless you can imagine a world in which, counter to facts, she did not hand you the apple.
8 Back to our H. sapiens ancestors: their newly acquired causal imagination enabled them to do many things more efficiently, through a tricky process we call planning. Imagine a tribe preparing for a mammoth hunt. What would it take for them to succeed? My mammoth-hunting skills are rusty, I must admit, but as a student of thinking machines I have learned one thing. The only way a thinking entity (computer, caveman, or professor) can accomplish a task of such magnitude is to plan things in advance. To decide how many hunters to recruit; to gauge, given The Book of Why: The New Science of Cause and Effect Pearl and Mackenzie 4 the wind conditions, what direction to approach the mammoth; and more. In short, to imagine and compare the consequences of several hunting strategies.
9 To do this, it must possess, consult, and manipulate a mental model of its reality. Here is how we might draw such a mental model: Figure 1. Perceived causes of a successful mammoth hunt. Each dot in the diagram represents a cause of success. Note that there are multiple causes, and that none of them are deterministic. That is, we cannot be sure that more hunters will enable us to succeed, or that rain will prevent us from succeeding; but these factors do change our probability of success. The mental model is the arena where imagination takes place. It enables us to experiment with different scenarios, by making local alterations to the model. Somewhere in our hunters mental model was a subroutine that evaluated the effect of the number of hunters.
10 When they considered adding more, they didn t have to evaluate every other factor from scratch. They could make a local change to the model, replacing Hunters = 8 by Hunters = 9 and re-evaluating the probability of success. This modularity is a key feature of causal models.. I don t mean to imply, of course, that early humans actually drew a pictorial model like this one. Of course not! But when we seek to emulate human thought on a computer, or indeed when we try to solve unfamiliar scientific problems, drawing an explicit dots-and-arrows picture The Book of Why: The New Science of Cause and Effect Pearl and Mackenzie 5 is extremely useful. You will see many in this book, and I will call them causal diagrams. They are the computational core of the causal inference engine described in Chapter 1.
